Vetted Version Control Professionals

“Built and shipped an LLM-powered data quality assistant that generates maintainable validation checks from metadata while executing validations via Great Expectations, exposed through FastAPI and integrated into Airflow-managed pipelines. Emphasizes production reliability (structured outputs, guardrails, monitoring, versioning, human review) and works closely with compliance/operations teams to deliver clear, auditable, user-friendly AI outputs.”

“Gameplay engineer with shipped mobile multiplayer experience on Squid Game: Unleashed, where they owned the Usable Items system end-to-end in Unity/C#. Built a modular ScriptableObject/action-based architecture that let designers create new item behaviors quickly without engineering support, while also handling network sync, prediction-related debugging, and internal validation tooling as the content library scaled.”

“Senior infrastructure/platform engineer with deep IBM Power/AIX (Power9, VIOS, HMC, LPAR/DLPAR) and PowerHA production ownership at scale (40 frames / ~300 LPARs), including hands-on outage recovery and performance tuning. Also delivers modern DevOps/IaC capabilities—CI/CD for Kubernetes microservices and Terraform-based multi-account AWS (EKS/VPC/IAM/RDS) with drift detection and safe rollout controls.”

Vinay Ramrupe

Screened

Mid AI/ML Engineer specializing in LLM and enterprise generative AI

San Francisco, CA5y exp

“ML/AI engineer focused on taking LLM systems from experimentation to reliable production, including enterprise copilot and RAG-based knowledge retrieval use cases. Stands out for combining data pipelines, model training, inference optimization, automated evaluation, and safety guardrails, with cited impact including 20% throughput gains and 30% less manual evaluation effort.”

Yuan-Hsuan Wen

Screened

Intern Software Engineer specializing in AI agents, RAG pipelines, and semiconductor systems

Taipei, Taiwan3y exp

“Built a web-based interface that connects an internal bug system to an LLM for initial debugging and issue classification, aiming to boost QA and software engineer efficiency while balancing latency and accuracy. Worked as a one-person project and managed constraints like limited hardware and difficulty extracting team debugging context, relying on manager communication and rapid modeling to validate direction.”

Joseph Fusco

Screened

Senior Software Engineer specializing in AI-powered developer tooling and backend platforms

Marin, CA10y exp

“Backend/product engineer from Postman Flows who has owned complex platform features end-to-end, including production versioning and an LLM-powered flow-building orchestration layer. Stands out for combining product-minded backend design, agentic AI workflow implementation, and strong production reliability work, including re-architecting a failing event pipeline from in-memory to managed queues.”

“ML/NLP engineer focused on production-grade data and search/recommendation systems: built an end-to-end pipeline that connects unstructured customer feedback with product data using TF-IDF/BERT, Spark, and AWS (SageMaker/S3), orchestrated with Airflow and monitored for drift. Also has hands-on experience with entity resolution at scale and improving search relevance via BERT embeddings, FAISS vector search, and domain fine-tuning validated with precision@k and A/B testing.”